code: def __init__(
      self,
      sorted_features: List[int],
      set_missing_value_to_zero: bool = False,
  ) -> None:
      super().__init__(sorted_features, set_missing_value_to_zero)
      self.feature_to_index: Dict[int, int] = {
          f: i for i, f in enumerate(sorted_features)
      }
  
file_path: ReAgent/reagent/preprocessing/sparse_to_dense.py
imports: from collections import defaultdict
  from typing import Dict, List, Tuple
  import torch
  from reagent.preprocessing import normalization
label_desc: Use image node_id 1 to create a new PythonSparseToDenseProcessor object from inherited base classes: SparseToDenseProcessor with example: obj = PythonSparseToDenseProcessor(sorted_features, set_missing_value_to_zero)